From 2568201d1b87c1187ccf0d0519671059b2d1ec5e Mon Sep 17 00:00:00 2001 From: Martin Bubel Date: Fri, 6 Oct 2023 08:12:38 +0200 Subject: [PATCH] format on save --- GPy/testing/grid_tests.py | 30 +++++++++++++++++++++++------- 1 file changed, 23 insertions(+), 7 deletions(-) diff --git a/GPy/testing/grid_tests.py b/GPy/testing/grid_tests.py index e55efb18..c6aaf049 100644 --- a/GPy/testing/grid_tests.py +++ b/GPy/testing/grid_tests.py @@ -7,13 +7,25 @@ import unittest import numpy as np import GPy + class GridModelTest(unittest.TestCase): def setUp(self): ###################################### # # 3 dimensional example # sample inputs and outputs - self.X = np.array([[0,0,0],[0,0,1],[0,1,0],[0,1,1],[1,0,0],[1,0,1],[1,1,0],[1,1,1]]) + self.X = np.array( + [ + [0, 0, 0], + [0, 0, 1], + [0, 1, 0], + [0, 1, 1], + [1, 0, 0], + [1, 0, 1], + [1, 1, 0], + [1, 1, 1], + ] + ) self.Y = np.random.randn(8, 1) * 100 self.dim = self.X.shape[1] @@ -33,10 +45,15 @@ class GridModelTest(unittest.TestCase): kernel2 = GPy.kern.RBF(input_dim=self.dim, variance=1, ARD=True) m2 = GPy.models.GPRegression(self.X, self.Y, kernel2) - np.testing.assert_almost_equal(kernel.variance.gradient, kernel2.variance.gradient) - np.testing.assert_almost_equal(kernel.lengthscale.gradient, kernel2.lengthscale.gradient) - np.testing.assert_almost_equal(m.likelihood.variance.gradient, m2.likelihood.variance.gradient) - + np.testing.assert_almost_equal( + kernel.variance.gradient, kernel2.variance.gradient + ) + np.testing.assert_almost_equal( + kernel.lengthscale.gradient, kernel2.lengthscale.gradient + ) + np.testing.assert_almost_equal( + m.likelihood.variance.gradient, m2.likelihood.variance.gradient + ) def test_prediction_match(self): kernel = GPy.kern.RBF(input_dim=self.dim, variance=1, ARD=True) @@ -45,7 +62,6 @@ class GridModelTest(unittest.TestCase): kernel2 = GPy.kern.RBF(input_dim=self.dim, variance=1, ARD=True) m2 = GPy.models.GPRegression(self.X, self.Y, kernel2) - test = np.array([[0,0,2],[-1,3,-4]]) + test = np.array([[0, 0, 2], [-1, 3, -4]]) np.testing.assert_almost_equal(m.predict(test), m2.predict(test)) -